The aioprocessing objects can be used just like their multiprocessing equivalents - as they are in func above - but they can also be seamlessly used inside of asyncio coroutines, without ever blocking the event loop. In most cases, this library makes blocking calls to multiprocessing methods asynchronous by executing the call in a ThreadPoolExecutor, using asyncio.run_in_executor(). It does not re-implement multiprocessing using asynchronous I/O. This means there is extra overhead added when you use aioprocessing objects instead of multiprocessing objects, because each one is generally introducing a ThreadPoolExecutor containing at least one threading.Thread. It also means that all the normal risks you get when you mix threads with fork apply here, too (See http://bugs.python.org/issue6721 for more info).